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Development and preliminary application of a gridded surface air temperature homogenized dataset for China

Xu, Yan, Zhao, Ping, Si, Dong, Cao, Lei, Wu, Xueyuan, Zhao, Yufei, Liu, Na
Theoretical and applied climatology 2020 v.139 no.1-2 pp. 505-516
air temperature, climate, data collection, latitude, longitude, models, China
When meteorological stations are quite unevenly distributed, a simple regional arithmetic mean of observation data may assign an excessive weight to one region with dense stations, which affects the representativeness of the regional mean. In this study, we used the homogenized monthly maximum (Tₘₐₓ), mean (Tₘ), and minimum (Tₘᵢₙ) temperature dataset at more than 2400 national surface meteorological stations in China. Based on a thin plate spline (TPS) interpolation method, we selected a three-dimensional (longitude, latitude, and elevation above sea level) interpolation model that is suitable for the temperature curve surface fitting in China, and constructed a gridded temperature dataset with a horizontal resolution of 0.5° during 1961 to 2015. Cross-validation indicates that the annual average of generalized cross-validation (GCV) is relatively small, and the ratio of GCV to the observed temperature is relatively low. Both the root of GCV and the root-mean-square error of temperature are smaller than those of the previous temperature gridded products. A comparison between our dataset and the Climate Research Unit (CRU) TS4.02 dataset indicates that the CRU’s data overestimate the warming trend in China during 1961–1984, whereas underestimate the warming trend during 1985–2015.